From c868fff5a2b41d3b76ec1101ed35dd5a4ddf9d26 Mon Sep 17 00:00:00 2001 From: amlrelsa-ms Date: Mon, 22 Feb 2021 19:23:04 +0000 Subject: [PATCH] update samples from Release-88 as a part of SDK release --- configuration.ipynb | 2 +- .../automated-machine-learning/automl_env.yml | 4 +- .../automl_env_linux.yml | 4 +- .../automl_env_mac.yml | 4 +- ...fication-bank-marketing-all-features.ipynb | 2 +- ...-ml-classification-credit-card-fraud.ipynb | 2 +- .../auto-ml-classification-text-dnn.ipynb | 2 +- .../auto-ml-continuous-retraining.ipynb | 2 +- .../experimental/automl_thin_client_env.yml | 6 +- .../automl_thin_client_env_mac.yml | 6 +- .../auto-ml-regression-model-proxy.ipynb | 118 ++++-------------- .../auto-ml-forecasting-beer-remote.ipynb | 2 +- .../auto-ml-forecasting-bike-share.ipynb | 2 +- .../auto-ml-forecasting-energy-demand.ipynb | 2 +- .../auto-ml-forecasting-function.ipynb | 2 +- ...to-ml-forecasting-orange-juice-sales.ipynb | 2 +- ...assification-credit-card-fraud-local.ipynb | 2 +- ...regression-explanation-featurization.ipynb | 2 +- .../regression/auto-ml-regression.ipynb | 20 ++- .../explain-model-on-amlcompute.ipynb | 2 +- ...ve-retrieve-explanations-run-history.ipynb | 4 +- ...ain-explain-model-locally-and-deploy.ipynb | 2 +- ...plain-model-on-amlcompute-and-deploy.ipynb | 4 +- ...urebatch-to-run-a-windows-executable.ipynb | 2 +- ...pipelines-how-to-use-pipeline-drafts.ipynb | 2 +- ...-publish-and-run-using-rest-endpoint.ipynb | 2 +- ...up-schedule-for-a-published-pipeline.ipynb | 6 +- ...s-setup-versioned-pipeline-endpoints.ipynb | 2 +- ...with-automated-machine-learning-step.ipynb | 4 +- ...pipelines-with-data-dependency-steps.ipynb | 2 +- .../pong_rllib.ipynb | 4 +- .../minecraft.ipynb | 4 +- .../logging-api/logging-api.ipynb | 2 +- .../train-local/train-local.ipynb | 2 +- .../train-remote/train-remote.ipynb | 2 +- setup-environment/configuration.ipynb | 2 +- 36 files changed, 76 insertions(+), 158 deletions(-) diff --git a/configuration.ipynb b/configuration.ipynb index c85736f9..afba9b3b 100644 --- a/configuration.ipynb +++ b/configuration.ipynb @@ -103,7 +103,7 @@ "source": [ "import azureml.core\n", "\n", - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/automl_env.yml b/how-to-use-azureml/automated-machine-learning/automl_env.yml index f10cb050..c927e618 100644 --- a/how-to-use-azureml/automated-machine-learning/automl_env.yml +++ b/how-to-use-azureml/automated-machine-learning/automl_env.yml @@ -21,9 +21,9 @@ dependencies: - pip: # Required packages for AzureML execution, history, and data preparation. - - azureml-widgets~=1.22.0 + - azureml-widgets~=1.23.0 - pytorch-transformers==1.0.0 - spacy==2.1.8 - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz - - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.22.0/validated_win32_requirements.txt [--no-deps] + - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.23.0/validated_win32_requirements.txt [--no-deps] - PyJWT < 2.0.0 diff --git a/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml b/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml index 70bf2f27..d9364b6f 100644 --- a/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml +++ b/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml @@ -21,10 +21,10 @@ dependencies: - pip: # Required packages for AzureML execution, history, and data preparation. - - azureml-widgets~=1.22.0 + - azureml-widgets~=1.23.0 - pytorch-transformers==1.0.0 - spacy==2.1.8 - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz - - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.22.0/validated_linux_requirements.txt [--no-deps] + - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.23.0/validated_linux_requirements.txt [--no-deps] - PyJWT < 2.0.0 diff --git a/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml b/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml index 3966fa56..bf1c46cb 100644 --- a/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml +++ b/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml @@ -22,9 +22,9 @@ dependencies: - pip: # Required packages for AzureML execution, history, and data preparation. - - azureml-widgets~=1.22.0 + - azureml-widgets~=1.23.0 - pytorch-transformers==1.0.0 - spacy==2.1.8 - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz - - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.22.0/validated_darwin_requirements.txt [--no-deps] + - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.23.0/validated_darwin_requirements.txt [--no-deps] - PyJWT < 2.0.0 diff --git a/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb b/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb index c40781af..41b399d7 100644 --- a/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb +++ b/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb @@ -105,7 +105,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb b/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb index d0a6cd14..6e9e39db 100644 --- a/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb +++ b/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb @@ -93,7 +93,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb b/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb index 5af772aa..ab1182fc 100644 --- a/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb +++ b/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb @@ -96,7 +96,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb b/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb index c4010566..56f9c66c 100644 --- a/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb +++ b/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb @@ -81,7 +81,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env.yml b/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env.yml index eb7913b9..554e53fe 100644 --- a/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env.yml +++ b/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env.yml @@ -5,17 +5,13 @@ dependencies: - pip<=19.3.1 - python>=3.5.2,<3.8 - nb_conda -- matplotlib==2.1.0 -- numpy~=1.18.0 - cython - urllib3<1.24 -- scikit-learn==0.22.1 -- pandas==0.25.1 - pip: # Required packages for AzureML execution, history, and data preparation. - azureml-defaults - azureml-sdk - azureml-widgets - - azureml-explain-model + - pandas - PyJWT < 2.0.0 diff --git a/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env_mac.yml b/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env_mac.yml index 765bfd70..64e0820c 100644 --- a/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env_mac.yml +++ b/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env_mac.yml @@ -6,17 +6,13 @@ dependencies: - nomkl - python>=3.5.2,<3.8 - nb_conda -- matplotlib==2.1.0 -- numpy~=1.18.0 - cython - urllib3<1.24 -- scikit-learn==0.22.1 -- pandas==0.25.1 - pip: # Required packages for AzureML execution, history, and data preparation. - azureml-defaults - azureml-sdk - azureml-widgets - - azureml-explain-model + - pandas - PyJWT < 2.0.0 diff --git a/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb b/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb index c4f248d8..f2366c38 100644 --- a/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb +++ b/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb @@ -67,11 +67,8 @@ "source": [ "import logging\n", "\n", - "from matplotlib import pyplot as plt\n", "import json\n", - "import numpy as np\n", - "import pandas as pd\n", - " \n", + "\n", "\n", "import azureml.core\n", "from azureml.core.experiment import Experiment\n", @@ -93,7 +90,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, @@ -116,9 +113,7 @@ "output['Resource Group'] = ws.resource_group\n", "output['Location'] = ws.location\n", "output['Run History Name'] = experiment_name\n", - "pd.set_option('display.max_colwidth', -1)\n", - "outputDf = pd.DataFrame(data = output, index = [''])\n", - "outputDf.T" + "output" ] }, { @@ -276,34 +271,13 @@ "## Results" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Widget for Monitoring Runs\n", - "\n", - "The widget will first report a \"loading\" status while running the first iteration. After completing the first iteration, an auto-updating graph and table will be shown. The widget will refresh once per minute, so you should see the graph update as child runs complete.\n", - "\n", - "**Note:** The widget displays a link at the bottom. Use this link to open a web interface to explore the individual run details." - ] - }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "from azureml.widgets import RunDetails\n", - "RunDetails(remote_run).show() " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "remote_run.wait_for_completion()" + "remote_run.wait_for_completion(show_output=True)" ] }, { @@ -368,18 +342,12 @@ "metadata": {}, "outputs": [], "source": [ - "# preview the first 3 rows of the dataset\n", - "\n", - "test_data = test_data.to_pandas_dataframe()\n", - "y_test = test_data['ERP'].fillna(0)\n", - "test_data = test_data.drop('ERP', 1)\n", - "test_data = test_data.fillna(0)\n", + "y_test = test_data.keep_columns('ERP')\n", + "test_data = test_data.drop_columns('ERP')\n", "\n", "\n", - "train_data = train_data.to_pandas_dataframe()\n", - "y_train = train_data['ERP'].fillna(0)\n", - "train_data = train_data.drop('ERP', 1)\n", - "train_data = train_data.fillna(0)\n" + "y_train = train_data.keep_columns('ERP')\n", + "train_data = train_data.drop_columns('ERP')\n" ] }, { @@ -397,7 +365,16 @@ "outputs": [], "source": [ "from azureml.train.automl.model_proxy import ModelProxy\n", - "best_model_proxy = ModelProxy(best_run)" + "best_model_proxy = ModelProxy(best_run)\n", + "y_pred_train = best_model_proxy.predict(train_data)\n", + "y_pred_test = best_model_proxy.predict(test_data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Exploring results" ] }, { @@ -406,60 +383,15 @@ "metadata": {}, "outputs": [], "source": [ - "y_pred_train = best_model_proxy.predict(train_data).to_pandas_dataframe().values.flatten()\n", + "y_pred_train = y_pred_train.to_pandas_dataframe().values.flatten()\n", + "y_train = y_train.to_pandas_dataframe().values.flatten()\n", "y_residual_train = y_train - y_pred_train\n", "\n", - "y_pred_test = best_model_proxy.predict(test_data).to_pandas_dataframe().values.flatten()\n", - "y_residual_test = y_test - y_pred_test" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "from sklearn.metrics import mean_squared_error, r2_score\n", - "\n", - "# Set up a multi-plot chart.\n", - "f, (a0, a1) = plt.subplots(1, 2, gridspec_kw = {'width_ratios':[1, 1], 'wspace':0, 'hspace': 0})\n", - "f.suptitle('Regression Residual Values', fontsize = 18)\n", - "f.set_figheight(6)\n", - "f.set_figwidth(16)\n", - "\n", - "# Plot residual values of training set.\n", - "a0.axis([0, 360, -100, 100])\n", - "a0.plot(y_residual_train, 'bo', alpha = 0.5)\n", - "a0.plot([-10,360],[0,0], 'r-', lw = 3)\n", - "a0.text(16,170,'RMSE = {0:.2f}'.format(np.sqrt(mean_squared_error(y_train, y_pred_train))), fontsize = 12)\n", - "a0.text(16,140,'R2 score = {0:.2f}'.format(r2_score(y_train, y_pred_train)),fontsize = 12)\n", - "a0.set_xlabel('Training samples', fontsize = 12)\n", - "a0.set_ylabel('Residual Values', fontsize = 12)\n", - "\n", - "# Plot residual values of test set.\n", - "a1.axis([0, 90, -100, 100])\n", - "a1.plot(y_residual_test, 'bo', alpha = 0.5)\n", - "a1.plot([-10,360],[0,0], 'r-', lw = 3)\n", - "a1.text(5,170,'RMSE = {0:.2f}'.format(np.sqrt(mean_squared_error(y_test, y_pred_test))), fontsize = 12)\n", - "a1.text(5,140,'R2 score = {0:.2f}'.format(r2_score(y_test, y_pred_test)),fontsize = 12)\n", - "a1.set_xlabel('Test samples', fontsize = 12)\n", - "a1.set_yticklabels([])\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "test_pred = plt.scatter(y_test, y_pred_test, color='')\n", - "test_test = plt.scatter(y_test, y_test, color='g')\n", - "plt.legend((test_pred, test_test), ('prediction', 'truth'), loc='upper left', fontsize=8)\n", - "plt.show()" + "y_pred_test = y_pred_test.to_pandas_dataframe().values.flatten()\n", + "y_test = y_test.to_pandas_dataframe().values.flatten()\n", + "y_residual_test = y_test - y_pred_test\n", + "print(y_residual_train)\n", + "print(y_residual_test)" ] }, { diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb index 30a1fe7b..f2572c95 100644 --- a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb +++ b/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb @@ -113,7 +113,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb index 92341f58..500c9627 100644 --- a/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb +++ b/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb @@ -87,7 +87,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb index 6ff32c0d..a5f910da 100644 --- a/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb +++ b/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb @@ -97,7 +97,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb index 3c66f1ac..8bb87b18 100644 --- a/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb +++ b/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb @@ -94,7 +94,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb index 5b05f82b..8b5d2dd6 100644 --- a/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb +++ b/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb @@ -82,7 +82,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb b/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb index 9da57318..bb7f1f95 100644 --- a/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb +++ b/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb @@ -96,7 +96,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb b/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb index 43687f44..3e9e0f5c 100644 --- a/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb +++ b/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb @@ -96,7 +96,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb b/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb index cdf74b2a..d56227b3 100644 --- a/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb +++ b/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb @@ -92,7 +92,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, @@ -375,18 +375,12 @@ "metadata": {}, "outputs": [], "source": [ - "# preview the first 3 rows of the dataset\n", - "\n", - "test_data = test_data.to_pandas_dataframe()\n", - "y_test = test_data['ERP'].fillna(0)\n", - "test_data = test_data.drop('ERP', 1)\n", - "test_data = test_data.fillna(0)\n", + "y_test = test_data.keep_columns('ERP').to_pandas_dataframe()\n", + "test_data = test_data.drop_columns('ERP').to_pandas_dataframe()\n", "\n", "\n", - "train_data = train_data.to_pandas_dataframe()\n", - "y_train = train_data['ERP'].fillna(0)\n", - "train_data = train_data.drop('ERP', 1)\n", - "train_data = train_data.fillna(0)\n" + "y_train = train_data.keep_columns('ERP').to_pandas_dataframe()\n", + "train_data = train_data.drop_columns('ERP').to_pandas_dataframe()\n" ] }, { @@ -396,10 +390,10 @@ "outputs": [], "source": [ "y_pred_train = fitted_model.predict(train_data)\n", - "y_residual_train = y_train - y_pred_train\n", + "y_residual_train = y_train.values - y_pred_train\n", "\n", "y_pred_test = fitted_model.predict(test_data)\n", - "y_residual_test = y_test - y_pred_test" + "y_residual_test = y_test.values - y_pred_test" ] }, { diff --git a/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.ipynb b/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.ipynb index 719c2f71..2b323fda 100644 --- a/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.ipynb +++ b/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.ipynb @@ -259,7 +259,7 @@ "run_config.environment.docker.enabled = True\n", "\n", "azureml_pip_packages = [\n", - " 'azureml-defaults', 'azureml-contrib-interpret', 'azureml-telemetry', 'azureml-interpret'\n", + " 'azureml-defaults', 'azureml-telemetry', 'azureml-interpret'\n", "]\n", "\n", "# Note: this is to pin the scikit-learn and pandas versions to be same as notebook.\n", diff --git a/how-to-use-azureml/explain-model/azure-integration/run-history/save-retrieve-explanations-run-history.ipynb b/how-to-use-azureml/explain-model/azure-integration/run-history/save-retrieve-explanations-run-history.ipynb index 11d291ff..46c68313 100644 --- a/how-to-use-azureml/explain-model/azure-integration/run-history/save-retrieve-explanations-run-history.ipynb +++ b/how-to-use-azureml/explain-model/azure-integration/run-history/save-retrieve-explanations-run-history.ipynb @@ -57,7 +57,7 @@ "Problem: IBM employee attrition classification with scikit-learn (run model explainer locally and upload explanation to the Azure Machine Learning Run History)\n", "\n", "1. Train a SVM classification model using Scikit-learn\n", - "2. Run 'explain_model' with AML Run History, which leverages run history service to store and manage the explanation data\n", + "2. Run 'explain-model-sample' with AML Run History, which leverages run history service to store and manage the explanation data\n", "---\n", "\n", "Setup: If you are using Jupyter notebooks, the extensions should be installed automatically with the package.\n", @@ -475,7 +475,7 @@ "metadata": {}, "outputs": [], "source": [ - "experiment_name = 'explain_model'\n", + "experiment_name = 'explain-model-sample'\n", "experiment = Experiment(ws, experiment_name)\n", "run = experiment.start_logging()\n", "client = ExplanationClient.from_run(run)" diff --git a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb index a7556a72..fcae079b 100644 --- a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb +++ b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb @@ -323,7 +323,7 @@ "\n", "# azureml-defaults is required to host the model as a web service.\n", "azureml_pip_packages = [\n", - " 'azureml-defaults', 'azureml-contrib-interpret', 'azureml-core', 'azureml-telemetry',\n", + " 'azureml-defaults', 'azureml-core', 'azureml-telemetry',\n", " 'azureml-interpret'\n", "]\n", " \n", diff --git a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.ipynb b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.ipynb index d960b4d2..ae1f2e52 100644 --- a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.ipynb +++ b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.ipynb @@ -267,7 +267,7 @@ "run_config.environment.python.user_managed_dependencies = False\n", "\n", "azureml_pip_packages = [\n", - " 'azureml-defaults', 'azureml-contrib-interpret', 'azureml-telemetry', 'azureml-interpret'\n", + " 'azureml-defaults', 'azureml-telemetry', 'azureml-interpret'\n", "]\n", " \n", "\n", @@ -431,7 +431,7 @@ "\n", "# WARNING: to install this, g++ needs to be available on the Docker image and is not by default (look at the next cell)\n", "azureml_pip_packages = [\n", - " 'azureml-defaults', 'azureml-contrib-interpret', 'azureml-core', 'azureml-telemetry',\n", + " 'azureml-defaults', 'azureml-core', 'azureml-telemetry',\n", " 'azureml-interpret'\n", "]\n", " \n", diff --git a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-how-to-use-azurebatch-to-run-a-windows-executable.ipynb b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-how-to-use-azurebatch-to-run-a-windows-executable.ipynb index 48b106db..f9f2d4c9 100644 --- a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-how-to-use-azurebatch-to-run-a-windows-executable.ipynb +++ b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-how-to-use-azurebatch-to-run-a-windows-executable.ipynb @@ -341,7 +341,7 @@ "outputs": [], "source": [ "pipeline = Pipeline(workspace=ws, steps=[step])\n", - "pipeline_run = Experiment(ws, 'azurebatch_experiment').submit(pipeline)" + "pipeline_run = Experiment(ws, 'azurebatch_sample').submit(pipeline)" ] }, { diff --git a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-how-to-use-pipeline-drafts.ipynb b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-how-to-use-pipeline-drafts.ipynb index eb7ccf41..0864a32b 100644 --- a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-how-to-use-pipeline-drafts.ipynb +++ b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-how-to-use-pipeline-drafts.ipynb @@ -130,7 +130,7 @@ "\n", "pipeline_draft = PipelineDraft.create(ws, name=\"TestPipelineDraft\",\n", " description=\"draft description\",\n", - " experiment_name=\"helloworld\",\n", + " experiment_name=\"pipeline_draft_sample\",\n", " pipeline=pipeline,\n", " continue_on_step_failure=True,\n", " tags={'dev': 'true'},\n", diff --git a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-publish-and-run-using-rest-endpoint.ipynb b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-publish-and-run-using-rest-endpoint.ipynb index 0bb96e22..ef552075 100644 --- a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-publish-and-run-using-rest-endpoint.ipynb +++ b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-publish-and-run-using-rest-endpoint.ipynb @@ -325,7 +325,7 @@ "outputs": [], "source": [ "# submit a pipeline run\n", - "pipeline_run1 = Experiment(ws, 'Pipeline_experiment').submit(pipeline1)\n", + "pipeline_run1 = Experiment(ws, 'Pipeline_experiment_sample').submit(pipeline1)\n", "# publish a pipeline from the submitted pipeline run\n", "published_pipeline2 = pipeline_run1.publish_pipeline(name=\"My_New_Pipeline2\", description=\"My Published Pipeline Description\", version=\"0.1\", continue_on_step_failure=True)\n", "published_pipeline2" diff --git a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-setup-schedule-for-a-published-pipeline.ipynb b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-setup-schedule-for-a-published-pipeline.ipynb index a3e276cb..7b479cb0 100644 --- a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-setup-schedule-for-a-published-pipeline.ipynb +++ b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-setup-schedule-for-a-published-pipeline.ipynb @@ -259,7 +259,7 @@ "\n", "schedule = Schedule.create(workspace=ws, name=\"My_Schedule\",\n", " pipeline_id=pub_pipeline_id, \n", - " experiment_name='Schedule_Run',\n", + " experiment_name='Schedule-run-sample',\n", " recurrence=recurrence,\n", " wait_for_provisioning=True,\n", " description=\"Schedule Run\")\n", @@ -445,7 +445,7 @@ "\n", "schedule = Schedule.create(workspace=ws, name=\"My_Schedule\",\n", " pipeline_id=pub_pipeline_id, \n", - " experiment_name='Schedule_Run',\n", + " experiment_name='Schedule-run-sample',\n", " datastore=datastore,\n", " wait_for_provisioning=True,\n", " description=\"Schedule Run\")\n", @@ -516,7 +516,7 @@ "\n", "schedule = Schedule.create_for_pipeline_endpoint(workspace=ws, name=\"My_Endpoint_Schedule\",\n", " pipeline_endpoint_id=published_pipeline_endpoint_id,\n", - " experiment_name='Schedule_Run',\n", + " experiment_name='Schedule-run-sample',\n", " recurrence=recurrence, description=\"Schedule_Run\",\n", " wait_for_provisioning=True)\n", "\n", diff --git a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-setup-versioned-pipeline-endpoints.ipynb b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-setup-versioned-pipeline-endpoints.ipynb index 4fc2d9cc..6544f352 100644 --- a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-setup-versioned-pipeline-endpoints.ipynb +++ b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-setup-versioned-pipeline-endpoints.ipynb @@ -553,7 +553,7 @@ "outputs": [], "source": [ "from azureml.core import Experiment\n", - "pipeline_run = Experiment(ws, name=\"submit_from_endpoint\").submit(pipeline_endpoint_by_name, tags={'endpoint_tag': \"1\"}, pipeline_version=\"0\")" + "pipeline_run = Experiment(ws, name=\"submit_endpoint_sample\").submit(pipeline_endpoint_by_name, tags={'endpoint_tag': \"1\"}, pipeline_version=\"0\")" ] } ], diff --git a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-with-automated-machine-learning-step.ipynb b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-with-automated-machine-learning-step.ipynb index ff4326f8..b86720cb 100644 --- a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-with-automated-machine-learning-step.ipynb +++ b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-with-automated-machine-learning-step.ipynb @@ -101,7 +101,7 @@ "metadata": {}, "source": [ "## Create an Azure ML experiment\n", - "Let's create an experiment named \"automlstep-classification\" and a folder to hold the training scripts. The script runs will be recorded under the experiment in Azure.\n", + "Let's create an experiment named \"automlstep-sample\" and a folder to hold the training scripts. The script runs will be recorded under the experiment in Azure.\n", "\n", "The best practice is to use separate folders for scripts and its dependent files for each step and specify that folder as the `source_directory` for the step. This helps reduce the size of the snapshot created for the step (only the specific folder is snapshotted). Since changes in any files in the `source_directory` would trigger a re-upload of the snapshot, this helps keep the reuse of the step when there are no changes in the `source_directory` of the step." ] @@ -113,7 +113,7 @@ "outputs": [], "source": [ "# Choose a name for the run history container in the workspace.\n", - "experiment_name = 'automlstep-classification'\n", + "experiment_name = 'automlstep-sample'\n", "project_folder = './project'\n", "\n", "experiment = Experiment(ws, experiment_name)\n", diff --git a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-with-data-dependency-steps.ipynb b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-with-data-dependency-steps.ipynb index facdca2f..10c0eed9 100644 --- a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-with-data-dependency-steps.ipynb +++ b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-with-data-dependency-steps.ipynb @@ -428,7 +428,7 @@ "metadata": {}, "outputs": [], "source": [ - "pipeline_run1 = Experiment(ws, 'Data_dependency').submit(pipeline1)\n", + "pipeline_run1 = Experiment(ws, 'Data_dependency_sample').submit(pipeline1)\n", "print(\"Pipeline is submitted for execution\")" ] }, diff --git a/how-to-use-azureml/reinforcement-learning/atari-on-distributed-compute/pong_rllib.ipynb b/how-to-use-azureml/reinforcement-learning/atari-on-distributed-compute/pong_rllib.ipynb index 3454c32c..f8e2dc8e 100644 --- a/how-to-use-azureml/reinforcement-learning/atari-on-distributed-compute/pong_rllib.ipynb +++ b/how-to-use-azureml/reinforcement-learning/atari-on-distributed-compute/pong_rllib.ipynb @@ -147,7 +147,7 @@ "\n", "To do this, you first must install the Azure Networking API.\n", "\n", - "`pip install --upgrade azure-mgmt-network`" + "`pip install --upgrade azure-mgmt-network==12.0.0`" ] }, { @@ -157,7 +157,7 @@ "outputs": [], "source": [ "# If you need to install the Azure Networking SDK, uncomment the following line.\n", - "#!pip install --upgrade azure-mgmt-network" + "#!pip install --upgrade azure-mgmt-network==12.0.0" ] }, { diff --git a/how-to-use-azureml/reinforcement-learning/minecraft-on-distributed-compute/minecraft.ipynb b/how-to-use-azureml/reinforcement-learning/minecraft-on-distributed-compute/minecraft.ipynb index 3c664b8c..b5cff26f 100644 --- a/how-to-use-azureml/reinforcement-learning/minecraft-on-distributed-compute/minecraft.ipynb +++ b/how-to-use-azureml/reinforcement-learning/minecraft-on-distributed-compute/minecraft.ipynb @@ -167,7 +167,7 @@ "\n", "To do this, you first must install the Azure Networking API.\n", "\n", - "`pip install --upgrade azure-mgmt-network`" + "`pip install --upgrade azure-mgmt-network==12.0.0`" ] }, { @@ -177,7 +177,7 @@ "outputs": [], "source": [ "# If you need to install the Azure Networking SDK, uncomment the following line.\n", - "#!pip install --upgrade azure-mgmt-network" + "#!pip install --upgrade azure-mgmt-network==12.0.0" ] }, { diff --git a/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb b/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb index d1acc681..3d153063 100644 --- a/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb +++ b/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb @@ -100,7 +100,7 @@ "\n", "# Check core SDK version number\n", "\n", - "print(\"This notebook was created using SDK version 1.22.0, you are currently running version\", azureml.core.VERSION)" + "print(\"This notebook was created using SDK version 1.23.0, you are currently running version\", azureml.core.VERSION)" ] }, { diff --git a/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-local/train-local.ipynb b/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-local/train-local.ipynb index 56938e47..06acf0a2 100644 --- a/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-local/train-local.ipynb +++ b/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-local/train-local.ipynb @@ -98,7 +98,7 @@ "metadata": {}, "outputs": [], "source": [ - "experiment_name = \"experiment-with-mlflow\"\n", + "experiment_name = \"LocalTrain-with-mlflow-sample\"\n", "mlflow.set_experiment(experiment_name)" ] }, diff --git a/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-remote/train-remote.ipynb b/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-remote/train-remote.ipynb index 001550ca..87432669 100644 --- a/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-remote/train-remote.ipynb +++ b/how-to-use-azureml/track-and-monitor-experiments/using-mlflow/train-remote/train-remote.ipynb @@ -123,7 +123,7 @@ "source": [ "from azureml.core import Experiment\n", "\n", - "experiment_name = \"experiment-with-mlflow\"\n", + "experiment_name = \"RemoteTrain-with-mlflow-sample\"\n", "exp = Experiment(workspace=ws, name=experiment_name)" ] }, diff --git a/setup-environment/configuration.ipynb b/setup-environment/configuration.ipynb index 443283f7..9dffd464 100644 --- a/setup-environment/configuration.ipynb +++ b/setup-environment/configuration.ipynb @@ -102,7 +102,7 @@ "source": [ "import azureml.core\n", "\n", - "print(\"This notebook was created using version 1.22.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.23.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] },